Showing 4 open source projects for "virtual windows machine"

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  • 1
    Netron

    Netron

    Visualizer for neural network, deep learning, machine learning models

    ...There is an extense variety of sample model files to download or open using the browser version. It is supported by macOS, Windows, Linux, Python Server and browser.
    Downloads: 67 This Week
    Last Update:
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    TenorSpace.js

    TenorSpace.js

    Neural network 3D visualization framework

    TensorSpace is a neural network 3D visualization framework built using TensorFlow.js, Three.js and Tween.js. TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information. After preprocessing the model, TensorSpace supports the visualization...
    Downloads: 1 This Week
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  • 3
    NN-SVG

    NN-SVG

    Publication-ready NN-architecture schematics

    Illustrations of Neural Network architectures are often time-consuming to produce, and machine learning researchers all too often find themselves constructing these diagrams from scratch by hand. NN-SVG is a tool for creating Neural Network (NN) architecture drawings parametrically rather than manually. It also provides the ability to export those drawings to Scalable Vector Graphics (SVG) files, suitable for inclusion in academic papers or web pages. The tool provides the ability to...
    Downloads: 1 This Week
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  • 4
    ConvNetJS

    ConvNetJS

    Deep learning in Javascript to train convolutional neural networks

    ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and...
    Downloads: 0 This Week
    Last Update:
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